Leads the design, development, and deployment of enterprise AI agents, copilots, predictive machine learning solutions, and scalable Python backend services. Builds RAG architectures, multi-agent workflows, APIs, data pipelines, and machine learning lifecycles. Integrates solutions with Microsoft Azure and Microsoft 365, supports cloud deployment and CI/CD, and establishes governance, monitoring, evaluation, security, and responsible AI practices.
The Senior AI Engineer will lead the design and implementation of AI-powered applications, intelligent agents, predictive analytics solutions, and scalable backend services. This role requires expertise in Python development, machine learning, enterprise AI platforms, cloud technologies, and API architecture.
You will collaborate with cross-functional teams to transform business requirements into secure, scalable, and production-ready solutions while ensuring alignment with enterprise governance and compliance standards.
Key Responsibilities:
Generative AI & Agent Development
Qualifications- Design, develop, and deploy enterprise-grade AI agents, copilots, and conversational applications.
- Implement multi-agent systems, tool-calling workflows, Retrieval-Augmented Generation (RAG) architectures, and prompt orchestration frameworks.
- Integrate AI solutions with Microsoft 365 technologies, including Teams, SharePoint, Outlook, Power Platform, Copilot Studio, and Microsoft Graph.
- Apply AI-assisted engineering practices to accelerate software delivery while maintaining code quality and security standards.
- Establish governance, monitoring, and evaluation frameworks for AI applications.
- Design and deploy predictive machine learning models for classification, regression, forecasting, and anomaly detection use cases.
- Build and maintain data pipelines supporting model development and deployment.
- Manage the end-to-end machine learning lifecycle, including feature engineering, training, validation, deployment, and monitoring.
- Collaborate with data engineering teams to develop scalable data solutions.
- Develop scalable APIs and backend services using Python frameworks such as FastAPI, Flask, or Django.
- Build maintainable, testable, and well-documented applications following modern software development practices.
- Participate in architecture reviews and technical design discussions.
- Support CI/CD implementation and cloud deployment strategies.
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related discipline.
- 8+ years of professional software development experience.
- Strong proficiency in Python, including object-oriented programming, asynchronous programming, and API development.
- Experience developing Generative AI applications using modern LLM platforms and agent frameworks.
- Experience implementing RAG architectures and vector database solutions.
- Strong understanding of machine learning concepts and hands-on experience with scikit-learn, pandas, NumPy, and PyTorch or TensorFlow.
- Experience building REST APIs and production-ready data pipelines.
- Experience with Microsoft Azure and Microsoft 365 integration technologies.
- Knowledge of software architecture, security, scalability, and enterprise integration patterns.
- Experience using Git-based development workflows and AI-assisted coding tools.
- Experience with Java and Spring Boot.
- Experience with Docker, Kubernetes, and CI/CD pipelines.
- Familiarity with MLOps platforms such as MLflow, Kubeflow, or Azure Machine Learning.
- Experience building enterprise copilots and AI assistants.
- Knowledge of AI evaluation frameworks, guardrails, observability, and responsible AI practices.
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